Agricultural and Forest Meteorology 125 (2004) 207–223 Seasonal variation and partitioning of ecosystem respiration in a southern boreal aspen forest
Bibliographic record
Abstract
Continuous automatic chamber and eddy covariance (EC) measurements were made at an old aspen forest (SOA) located at southern boreal treeline in Saskatchewan, Canada to examine the temporal variability in soil (Rs), tree bole (Rb), and ecosystem respiration (RE) during 2001. Climatic conditions were significantly warmer and drier than the 30-year climate normal, resulting in lower RE and an unprecedented increase in net ecosystem productivity (NEP). In the 7-year record (1994, and 1996–2001) of CO2 exchange at SOA, the year 2001 showed the greatest carbon gain (300 g C m−2 year). Scaled chamber measurements (1315 g C m−2 per year) were 37 % larger than the EC estimate of RE (961 g C m−2 per year). The difference between the scaled chambers and the EC estimate was reduced to 20 % after correcting for lack of energy bal-ance closure. Annual RE was approximately 170 g C m−2 per year lower than the average of the previous 6 years. Annual estimates of microbial-heterotrophic (Rh) (510 g C m−2 per year) and autotrophic respiration (Ra) (805 g C m−2 per year), based on chamber measurements, were used to help validate the EC estimate of RE. Ra represented 61 % of the total chamber respiration. This fraction was used to partition RE into Ra and Rh to calculate net primary production (NPP). The values of NEP (300 g C m−2 per year) and NPP (675 g C m−2 per year) were more characteristic of temperate forests. The NPP/Pg ratio of 0.54 was within the range of recently published values using biometric techniques and supports that the annual ecosystem respiration budget and its partitioning was well constrained. We recognize, however, that this ratio will vary
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".